Women's Crimes in India

Characteristics, Frequency, and Motives

By Rajanand Ilangovan [source]

About this dataset

This dataset contains extensive information about various types of crimes that happened in India from 2001 to 2019. Using this dataset, one can gain a deep insight into the crime trend and various factors that can be identified for analysing it. From Area_Name, Year, Sub_Group and CPA Cases Registered to Persons Acquitted- This dataset covers almost every single aspect of Crime against women in India while also giving a glance at other related aspects such as Auto-Theft Coordinated or Traced and Trials completed by courts. It is immensely helpful in understanding the crime patterns of India over time and make predictions accordingly

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How to use the dataset

Using this dataset, we can gain unparalleled insight into the prevalence and distribution of crimes against women over this period in different parts across India as well as within each state. This could be used for further research into the social impact on certain areas with heightened crime rates or for governmental organizations striving for initiatives to combat such criminal activities.

Research Ideas

• Analyzing patterns in violent crimes against women and children, such as the number of reported cases, total convictions and acquittals.
• Examining trends in different types of crime by state or city over time to identify hotspots or regional crime issues.
• Comparing police personnel performance to analyze effectiveness of action taken against certain types of crime in different areas over time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: 25_Complaints_against_police.csv | Column name | Description | |:--------------------------------------------------------------------|:-------------------------------------------------------------------------------| | Area_Name | Name of the area where the crime was committed. (String) | | Year | Year in which the crime was committed. (Integer) | | Sub_group | Type of crime committed. (String) | | CPA_-_Cases_Registered | Number of cases registered in the given year. (Integer) | | CPA_-_Cases_Reported_for_Dept._Action | Number of cases reported to the department for action. (Integer) | | CPA_-_Complaints/Cases_Declared_False/Unsubstantiated | Number of complaints/cases declared false or unsubstantiated. (Integer) | | CPA_-_Complaints_Received/Alleged | Number of complaints received or alleged. (Integer) | | CPA_-_No_of_Departmental_Enquiries | Number of departmental enquiries. (Integer) | | CPA_-_No_of_Magisterial_Enquiries | Number of magisterial enquiries. (Integer) | | CPA-_Cases_Sent_for_Trials/Charge-sheeted | Number of cases sent for trial or charge-sheeted. (Integer) | | CPA-_No_of_Judicial_Enquiries | Number of judicial enquiries. (Integer) | | CPB_-_Police_Personnel_Acquitted | Number of police personnel acquitted. (Integer) | | CPB_-_Police_Personnel_Convicted ...

Prison Inmates in India

Demographics, Age, Education, Caste, Wages, Rehabilitation, Technical Info

By Rajanand Ilangovan [source]

About this dataset

This dataset provides a detailed view of prison inmates in India, including their age, caste, and educational background. It includes information on inmates from all states/union territories for the year 2019 such as the number of male and female inmates aged 16-18 years, 18-30 year old inmates and those above 50 years old. The data also covers total number of penalized prisoners sentenced to death sentence, life imprisonment or executed by the state authorities. Additionally, it provides information regarding the crimehead (type) committed by an inmate along with its grand total across different age groups. This dataset not only sheds light on India’s criminal justice system but also highlights prevelance of crimes in different states and union territories as well as providing insight into crime trends across Indian states over time

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How to use the dataset

This dataset provides a comprehensive look at the demographics, crimes and sentences of Indian prison inmates in 2019. The data is broken down by state/union territory, year, crime head, age groups and gender.

This dataset can be used to understand the demographic composition of the prison population in India as well as the types of crimes committed. It can also be used to gain insight into any changes or trends related to sentencing patterns in India over time. Furthermore, this data can provide valuable insight into potential correlations between different demographic factors (such as gender and caste) and specific types of crimes or length of sentences handed out.

To use this dataset effectively there are a few important things to keep in mind: •State/UT - This column refers to individual states or union territories in India where prisons are located •Year – This column indicates which year(s) the data relates to •Both genders - Female columns refer only to female prisoners while male columns refers only to male prisoners •Age Groups – 16-18 years old = 21-30 years old = 31-50 years old = 50+ years old •Crime Head – A broad definition for each type of crime that inmates have been convicted for •No Capital Punishment – The total number sentenced with capital punishment No Life Imprisonment – The total number sentenced with life imprisonment No Executed– The total number executed from death sentence Grand Total–The overall totals for each category

By using this information it is possible to answer questions regarding topics such as sentencing trends, types of crimes committed by different age groups or genders and state-by-state variation amongst other potential queries

Research Ideas

• Using the age and gender information to develop targeted outreach strategies for prisons in order to reduce recidivism rates.
• Creating an AI-based predictive model to predict crime trends by analyzing crime head data from a particular region/state and correlating it with population demographics, economic activity, etc.
• Analyzing the caste of inmates across different states in India in order to understand patterns of discrimination within the criminal justice system

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: SLL_Crime_headwise_distribution_of_inmates_who_convicted.csv | Column name | Description | |:--------------------------|:---------------------------------------------------------------------------------------------------| | STATE/UT | Name of the state or union territory where the jail is located. (String) | | YEAR | Year when the inmate population data was collected. (Integer) ...

Saudi Arabia SA: Intentional Homicides: Female: per 100,000 Female data was reported at 1.145 Ratio in 2015. Saudi Arabia SA: Intentional Homicides: Female: per 100,000 Female data is updated yearly, averaging 1.145 Ratio from Dec 2015 (Median) to 2015, with 1 observations. Saudi Arabia SA: Intentional Homicides: Female: per 100,000 Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.World Bank: Health Statistics. Intentional homicides, female are estimates of unlawful female homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.; ; UN Office on Drugs and Crime's International Homicide Statistics database.; ;

This dataset is from the SAFE study, focusing on developing and evaluating an eHealth intervention for women in the Netherlands who experience intimate partner violence and abuse (IPVA). The first goal was to assess needs, wishes and obstacles with regard to an eHealth intervention in the context of IPVA and to develop an eHealth intervention for women who experience IPVA. This, together with scientific literature and similar interventions in the IPVA context, inspired the content and functionalities of the SAFE intervention. Then, we aimed for the intervention to increase self-efficacy, awareness and perceived support and to decrease anxiety and depression symptoms amongst its users: women (18-50 years old) who experience IPVA. Also, we aimed for the intervention to encourage women in help seeking, and that the intervention would be a suitable tool to deliver information and support its users.For the development phase, we interviewed women IPVA victims/survivors (18+) and professionals in the field of domestic violence and abuse (DVA) and IPVA (N=16; published study: https://journals.sagepub.com/doi/10.1177/08862605211036108). The eHealth intervention SAFE was launched in April 2019 and simultaneously gathering data for the RCT and process evaluation, aimed at evaluating the intervention, started. For the RCT, after the participant gave their consent (digitally), we followed women (18-50 years old) for 6 or 12 months (depending on when they were included; see protocol article for more info: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0) and gathered data on multiple timepoints: baseline (M0/T0, at registration; N=198), 3 months (M3/T1), 6 months (M6/T2), and 12 months (M12/T3). The RCT study had two study arms: control group and intervention group. With the intervention group receiving a more elaborate and interactive intervention than the control group (see protocol article for additional information on the content of the intervention). All RCT data was gathered online, with questionnaires on demographic data, on their IPVA experience, and with the primary outcome being self-efficacy at M6 (measured with the General Self-Efficacy Scale (GSE)). Examples of secondary outcomes are anxiety and depression (measured with the Hospital Anxiety and Depression Scale (HADS)). The process evaluation included quantitative and qualitative data. Quantitative from the Web Evaluation Questionnaire (WEQ) that assessed how users graded the intervention, if they felt it was safe and easy to use etc. WEQ data was gathered at one month after the first login (M1), 3 months (M3) and 6 months (M6) after registering for SAFE. The qualitative data consists of interviews with participants from the RCT intervention study arm: N=10. The semi-structured interviews focused on the users' experiences with and opinions on the SAFE eHealth intervention.Data are in Dutch. Two sets of interview data: one from the development phase and one from the process evaluation. Two Excel documents with the final codebooks for the two interview studies. Two SPSS datasets for the RCT and process evaluation. Data are anonymized and pseudonymized to ensure the participants' safety and privacy. All participants provided (digital) informed consent before participating.- Interview data development phase (with survivors / victims and professionals): gathered in 2018, in person interviews, N=16. Publication: https://journals.sagepub.com/doi/10.1177/08862605211036108- Interview data process evaluation (with participants from the RCT intervention study arm): gathered in 2021, online interviews, N=10. No publication yet.- SPSS data RCT (with a control and intervention study arm): gathered in 2019-2021, via online questionnaires (e.g. demographic data, General Self-Efficacy Scale, Hospital Anxiety and Depression Scale, Bem Sex Role Inventory, Medical Outcomes Study Social Support 5), N=198 at baseline. No publication yet. Protocol: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0- SPSS data process evaluation: gathered in 2019-2021, via online questionnaire (Web evaluation questionnaire). No publication yet. Protocol: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0Methodology interview data: semi-structured interviews, open thematic coding in Atlas.ti, with 2 or 3 researchers coding independently, qualitative content analysis, grounded theory.Methodology questionnaire data: use of validated questionnaires, analyzing in SPSS: descriptive statistics, check for selective attrition bias, T-tests, ANCOVA, GEE. Data from the development process (interviews), RCT and process evaluation

Number of people (levels), men and women made redundant and redundancy rates, seasonally adjusted. These estimates are sourced from the Labour Force Survey, a survey of households. These are official statistics in development.

L'intérêt porté au thème de la violence contre les femmes connaît une forte expansion depuis deux décennies. Au cours des années quatre-vingt-dix, et suite à des études sur le sujet au Canada et aux Etats-Unis, l'attention fut portée sur la violence contre les femmes en général, et non plus exclusivement sur celle survenant au sein de la relation de couple. Suite aux travaux préparatoires de deux instituts de l'ONU (UNICRI à Turin et HEUNI à Helsinki), et une fois la méthode uniformisée (un questionnaire et une méthode d'enquête identiques), des études nationales sur cette problématique ont été prévues dans environ 30 pays. L'enquête suisse s'appuie sur l'interview par téléphone, entre avril et août 2003, de 1975 femmes âgées de 18 à 70 ans et vivant en Suisse alémanique et en Romandie. L'échantillon ainsi obtenu est représentatif de la population féminine. La méthode utilisée fut l'enquête par téléphone assistée par ordinateur, qui s'était déjà montrée adéquate lors des précédentes enquêtes de victimisation. Ce choix fut également motivé par la grande complexité du questionnaire. Ce dernier devait en effet permettre d'appréhender différentes catégories de violence, s'inscrivant dans différents types de relation entre l'auteur et sa victime (mariage, concubinage, anciens partenaires, collègues, inconnus), et ce depuis l'âge de 16 ans (les expériences vécues dans l'enfance n'étant pas prises en compte). Les objectifs de cette recherche étaient multiples: - accroître la conscience de ce problème chez les autorités comme parmi le public - promouvoir la prévention face à cette problématique - fournir des informations fiables pour le développement de législations, politiques et moyen d'aide aux victimes - mettre sur pied une base de données internationalement comparable - aider la police dans ses pratiques de travail dans ce domaine - formuler et tester certaines hypothèses A ce titre, voici quelles étaient les hypothèses et questions de recherche: - Quelle est l'étendue de ce type de violence en Suisse, comparé à d'autres pays? Comment expliquer ces différences? - Comment a évolué la situation de la violence domestique depuis l'étude de Gillioz et al. (1994)? - Quelle est l'importance de différents facteurs, notamment situationnels et biographiques dans les expériences de violence? - Quelle est l'influence du parcours criminel passé et actuel de l'homme sur sa tendance à la violence conjugale? - Quels effets d'interaction particuliers se révèlent parmi les variables étudiées? - Comment est perçu le rôle de la police parmi les victimes? - L'aide (institutionalisée) aux victimes atteint-elle ses objectifs? Interest in the topic of violence against women has grown strongly over the last two decades. During the nineties, and following studies on the subject in Canada and the United States, the focus has shifted to violence against women in general, and no longer exclusively on domestic violence against women. Following the preparatory work of two UN institutes (UNICRI in Turin and HEUNI in Helsinki), and once the method had been standardized (identical questionnaire and survey method), national studies on this issue have been planned in approximately 30 countries. The Swiss survey is based on a telephone interview, between April and August 2003, of 1975 women aged 18 to 70 living in the German-speaking and the French-speaking parts of Switzerland. The sample thus obtained is representative of the female population. The method used was the computer-assisted telephone survey, which had already proved adequate in previous victimization surveys. This choice was also motivated by the great complexity of the questionnaire. The latter should indeed allow to apprehend different categories of violence, relating to different types of relationship between the author and his victim (marriage, cohabitation, former partners, colleagues, strangers) since the age of 16 years (experiences lived in childhood are not taken into account). There are several objectives for this study: - to increase the awareness of this problem among the authorities and the public - to promote prevention - to provide reliable information for the development of legislation, policies and means of assistance to victims - to set up an internationally comparable database - to help the police in their work practices concerning violence against women - to formulate and test certain hypotheses On thjs basis, here are the hypotheses and research questions: - What is the extent of this type of violence in Switzerland, compared to other countries? How to explain these differences? - How has the situation of domestic violence evolved since the study by Gillioz et al. (1994)? - How important are various factors, including situational and biographical, in experiences of violence? - What is the influence of the past and current criminal history of men on their tendency to domestic violence? - What particular interaction effects are revealed among the variables studied? - How is the role of the police perceived among the victims? - Does (institutionalized) aid to victims achieve its objectives?